A typical metallic product manufacturing process chain involving several companies faces challenges in promptly responding to the deviations in material properties, thereby impacting its economic efficiency. This can be attributed to the lack of knowledge about the exact condition of each product in a batch, as suppliers can only perform quality inspections randomly. This study introduces a novel approach utilizing simulation models to calculate the mechanical properties of products and design of experiments based process design using the calculated product properties shared by suppliers with their customers over a secure and reliable intercompany data management platform. The proposed approach is implemented in a laboratory scale process chain consisting of cold rolling and deep drawing using DC04 steel to demonstrate adaptive process control via intercompany exchange of yield and tensile strength of the cold strip. The benefits of adaptive process control are demonstrated by 50 % reduction in deviations in the minimum sheet thickness in cross die, thus showcasing the reproducibility of the end product with improved quality and by avoiding scrap generation, thereby allowing a sustainable manufacturing.
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Thakare et al. (2025) studied this question.